Review recordation and evaluation systems and methods

ABSTRACT

A computer-implemented system and method for generating and displaying an authority score through a software application executed by a process or a computing device. The processor may receive visit data indicative of a user&#39;s presence and review data describing an entity at a location. The processor may determine an authority score for the review data and perform a calculation using at least a portion of the visit data as at least one input. The processor may generate and cause a visual indication of the authority score to be displayed by a display device.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority from U.S. Provisional Application No.62/916,893, filed Oct. 18, 2019, and entitled “Review Recordation andEvaluation Systems and Methods”, the entire contents of which are hereinincorporated by reference.

SUMMARY

In accordance with some embodiments of the present disclosure, there isprovided a method for generating and displaying an authority score. Themethod can include receiving visit data indicative of a user's presenceat a location and receiving review data describing an entity at thelocation by at least one processor. The method can include determiningan authority score for the review data by the at least one processor.The determining an authority score for the review data can includeperforming a calculation using at least a portion of the visit dataand/or review data as at least one input by the at least one processor.The method can also include generating a visual indication of theauthority score, the visual indication having at least one visualcharacteristic determined by at least one outcome of the calculation ofthe at least one processor. The method can further include causing thevisual indication to be displayed by a display device, by the at leastone processor.

Furthermore, in accordance with some embodiments of the presentdisclosure, there is provided a system for generating and displaying anauthority score. The system can include a display device and at leastone processor in communication with the display device. The at least oneprocessor can be configured to receive visit data indicative of a user'spresence and receive review data describing an entity at a location. Theat least one processor can be configured to determine an authority scorefor the review data. The determining can include performing acalculation using at least a portion of the visit data and/or reviewdata as at least one input and generating a visual indication of theauthority score by the at least one processor. The visual indication canhave at least one visual characteristic determined by at least oneoutcome of the calculation.

Furthermore, in accordance with some embodiments of the presentdisclosure, there is provided a method for generating and displaying anauthority score. The method can include receiving review data describingan entity at the location. The method can include determining anauthority score for the review data by the at least one processor. Thedetermining an authority score for the review data can includeperforming a calculation by the at least one processor. The method canalso include generating a visual indication of the authority score. Thevisual indication can have at least one visual characteristic determinedby at least one outcome of the calculation of the at least oneprocessor. The method can further include causing the visual indicationto be displayed by a display device by the at least one processor.

Furthermore, in accordance with some embodiments of the presentdisclosure, there is provided a system for generating and displaying anauthority score. The system can include a display device and at leastone processor in communication with the display device. The at least oneprocessor can be configured to receive review data describing an entityat the location. The at least one processor can be configured todetermine an authority score for the review data. The determiningincludes performing a calculation and generating a visual indication ofthe authority score by the at least one processor. The visual indicationhas at least one visual characteristic determined by at least oneoutcome of the calculation.

The foregoing and other aspects of embodiments are described in furtherdetail with reference to the accompanying drawings, in which the sameelements in different figures are referred to by common referencenumerals. The embodiments are illustrated by way of example and shouldnot be construed to limit the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A illustrates an example computing system in accordance with someembodiments of the present disclosure.

FIG. 1B is a flowchart illustrating an example process for generatingand displaying an authority score of reviews through a softwareapplication in accordance with some embodiments disclosed herein.

FIG. 1C is a flowchart illustrating another example process forgenerating and displaying authority score of reviews through a softwareapplication in accordance with some embodiments disclosed herein.

FIG. 2A is a flowchart illustrating an example process for capturing andrecording visit data in accordance with some embodiments disclosedherein.

FIG. 2B is a flowchart illustrating an example process of a pollingmethod for capturing and recording data in accordance with someembodiments disclosed herein.

FIG. 3 is a flowchart illustrating an example process for capturingbeacon data in accordance with some embodiments disclosed herein.

FIG. 4 is a flowchart illustrating an example process for claiming avenue and registering a Bluetooth beacon in accordance with someembodiments disclosed herein.

FIG. 5 is a flowchart illustrating an example process for registering abeacon in accordance with some embodiments disclosed herein.

FIG. 6 is a flowchart illustrating an example method for transmittingvisit data in accordance with some embodiments disclosed herein.

FIG. 7 is a flowchart illustrating an example process for capturing areview created by a user in accordance with some embodiments disclosedherein.

FIG. 8 is a flowchart illustrating an example process for evaluating thedata to establish the review metrics in accordance with some embodimentsdisclosed herein.

FIG. 9A is a flowchart illustrating an example process for utilizing analgorithm which emphasises beacon data matches and location data matchesand adjusts for recency of visit in accordance with some embodimentsdisclosed herein.

FIG. 9B is a flowchart corresponding to FIG. 9A with example values inaccordance with some embodiments disclosed herein.

FIG. 10A is a flowchart illustrating another example process forutilizing an algorithm similar to that illustrated in FIG. 9A which alsoadjusts for the length of the visit compared to the average length ofvisits according to some embodiments disclosed herein.

FIG. 10B is a flowchart corresponding to FIG. 10A with example valuesaccording to some embodiments disclosed herein.

FIG. 11A is a flowchart illustrating an example process for utilizing analgorithm to give more emphasis to reviews created within theapplication at the time of the visit rather than those added after thevisit according to some embodiments disclosed herein.

FIG. 11B is a flowchart corresponding to FIG. 11A with example valuesaccording to some embodiments disclosed herein.

FIG. 12A is a flowchart illustrating an example process for utilizing anexample algorithm similar to that illustrated in FIG. 9A but which takesa different approach to setting base scores according to someembodiments disclosed herein.

FIG. 12B is a flowchart corresponding to FIG. 12A with example valuesaccording to some embodiments disclosed herein.

FIG. 13 is a flowchart illustrating an example process for displayingthe authority score and the user rating according to some embodimentsdisclosed herein.

FIG. 14 shows an example graphical representation of the user ratingsaccording to some embodiments disclosed herein.

FIG. 15 is a block diagram of an example computing device utilized toexecute some embodiments disclosed herein.

DETAILED DESCRIPTION

Embodiments described herein may include a method to generate anddisplay an authority score representing the authority, trustworthinessor reliability of reviews recorded through a computer softwareapplication executed by a computing device.

FIG. 1A illustrates an example computing system 100A for generating anddisplaying an authority score of reviews in accordance with thedisclosed principles. The computing system 100 may include a servercomputing device 120 (e.g., a server), one or more user computingdevices 130 in communication with the server computing device 120, aplurality of beacons 140 and a network 150. The server computing device120 may include a processor 121, a memory 122 and a communicationinterface for enabling communications with other computing devices overnetwork 150. Network 150 may include the Internet and/or other public orprivate networks or combinations thereof.

The server computing device 120 may host an online service or softwareapplication 123 stored in the memory 122. The software application 123may be configured to include computer-executable instructions forimplementing processes, systems and embodiments described in the presentdisclosure. The computer-executable instructions may be stored in amemory communicatively coupled to and executed by the processor 121 toperform one or more methods for generating an authority score ofreviews.

Database 124 may be a database included in or being coupled to theserver 120. The database 124 may be a local database in communicationwith the processor 121 of the server 120 via the network 150. Database124 may be configured to receive, store and update visit data 125 (e.g.,which may include location data, beacon data, and/or other data asdescribed below), review data 126 (e.g., which may include user rating,review text, media data and authority scores of reviews as describedbelow) and venue data 127.

A user computing device 130 may include a processor 131 and a memory132. The user computing device 130 or a client device may be a mobilecomputing device, such as a smartphone, tablet, and/or any types ofother computing device. In some embodiments, a software application 133may be a mobile application installed and executed by a processor 131 ofa mobile device 130. In some embodiments, a software application 133 maybe a web browser application run on the user computing device 130 toaccess the application 123 on the server 120 for performing operationsand processes described herein.

Different processes described herein may be configured as one or morecomputer programs (e.g., application 123 and/or application 133)executed on the server 120 or user computing devices, in which thesystems, processes, and embodiments described below can be implemented.The order of the operations described in each process is not intended tobe construed as a limitation, and any number of the described operationscan be combined in any order and/or in parallel to implement eachprocess described herein.

FIG. 1B is a flowchart illustrating an example process 100B forgenerating and displaying an authority score of reviews through asoftware application.

At 102, the application 133 may capture location data and the presenceof beacons (‘visit data’) (102). At 1022, a venue's administrator mayclaim a venue (1022) so that the venue administrator registers andconfigures Bluetooth beacons at their premises (1024). At 104, theapplication 133 may transmit the location and beacon data to servers120. At 106, the application 133 may capture reviews from users. At 108,the server may analyse the review data to establish the review metrics.At 110, the server may use the review metrics to calculate and generatean authority score. At 112, the server may optionally use comparativedata to refine the authority score. At 114, the server may return theauthority score with the user rating to the application. At 116, theapplication 133 may display the authority score with the user rating inone graphic. At 118, the server may store the generated score in thedatabase 124 to update the authority scores of previous reviews.Optionally, the server 120 may re-evaluate previous authority scores.

The application 133 may record location data and the presence of beaconsor other external devices. The location data may include longitude andlatitude data. Location data may be periodically captured both when theapplication 133 is running the foreground and or when it is running inthe background. However, the frequency of collection may be dependent onthe rate allowed by the operating system, which can differ when theapplication 133 is in the background.

FIG. 10 is a flowchart illustrating another example process 100C forgenerating and displaying authority score of reviews through a softwareapplication.

At 110C, the processor 121 of the server 120 may receive visit data 125indicative of a user's presence at a location. The visit data 125 mayinclude an indication of the location, a duration of the user'spresence, a time of the user's presence, a record of a previous visit,an activity performed at the location, an indication of a beacondetection by a client device at the location, or a combination thereof.Details about capturing, receiving and recording visit data 125 will bedescribed in FIGS. 2A-2B and FIGS. 4-5 below.

At 120C, the processor 121 of the server 120 may receive review datadescribing an entity at the location. The review data may include atextual review, a rating score, a media element, or a combinationthereof. Details about receiving and transmitting review data will bedescribed in FIGS. 6-8 below.

At 130C, the processor 121 of the server 120 may determine an authorityscore for the review data. Determining the authority score for thereview data may include performing a calculation using at least aportion of the visit data 125 as at least one input. Details aboutdetermining an authority score for the review data will be described inFIGS. 9A-9B, 10A-10 b, 11A-11B and 12A-12B below.

In one or more embodiments, determining the authority score may includecorrelating the indication of the location with a record of the locationof the entity. In one or more embodiments, determining the authorityscore may include correlating the beacon detection with a record of thelocation of the entity. In one or more embodiments, determining theauthority score may include determining a location at which the mediaelement was captured and correlating the location at which the mediaelement was captured with a record of the location of the entity.

In one or more embodiments, the calculation may be configured so thatthe authority score increases with an increase in the duration. In oneor more embodiments, the calculation is configured so that the authorityscore decreases with an increase in a difference between a time at whichthe visit data 125 is received and the time of the user's presence.

At 140C, the processor 121 of the server 120 may generate a visualindication of the authority score. The visual indication may have atleast one visual characteristic determined by at least one outcome ofthe calculation. The at least one visual characteristic may include afirst shaded or colored area and a second shaded or colored area, andthe calculation may be configured so that a contrast between the firstshaded or colored area and the second shaded or colored area increasesas the authority score increases. The at least one visual characteristicmay include a first shaded or colored area and a background. In at leastsome embodiments, the calculation may be configured so that a visibilityof the first shaded or colored area against the background increases asthe authority score increases. Other modes of displaying the authorityscore may be employed in other embodiments, as described in detailbelow.

At 150C, the processor 121 of the server 120 may cause the visualindication to be displayed by a display device. Details about generatingand displaying a visual indication of the authority score will bedescribed in FIGS. 13-14 below.

FIG. 2A is a flowchart illustrating an example process for capturing andrecording visit data 125. The application 133 may record location datausing a notification subsystem. When using a notification subsystem, theapplication 133 may generate a subscription to an operating system'slocation notification API (202). The operating system's locationnotification API may notify the application 133 of the last knownlocation data as per the operating system rules (204). The application133 may record the location data in a local database along with atimestamp of when the data was captured (206).

FIG. 2B is a flowchart illustrating an example process of a pollingmethod for capturing and recording location data. The application 133may capture and record location data using a polling method depending onwhat is supported by the operating system and the permissions granted tothe application 133 by a user. When using a polling method, theapplication 133 may generate a background task to poll the operatingsystem's location API for the current (or last known) location data ofthe device (208). The application 133 may record the location data in alocal database 124 along with a timestamp of when the data was captured(210).

FIG. 3 is a flowchart illustrating an example process for capturingbeacon data. The application 133 may record beacon data to represent thepresence of Bluetooth beacons that have been issued by a business entityor other entity. For example, the application 133 installed on themobile device 130 may be executed to create or generate a subscriptionto the operating system's beacon detection API, using a UniversallyUnique Identifier (UUID) to distinguish beacons (e.g., beaconsassociated with the systems and methods described herein) from othersenders' beacons (302). In various embodiments, the UUID may include atleast a UUID assigned to the entity that has issued the beacon (e.g., anentity UUID). The UUID may be broadcasted and detected by theapplication 133 or operating system running on a user mobile device todetermine the presence of the beacon in the vicinity of the user mobiledevice 130. A beacon detection API may trigger a detection event on theuser mobile device 130 (304). Upon a detection event of a beacon withthe entity UUID being triggered, the operating system's beaconnotification API may notify the application 133 of the beaconidentifying details (306). The application 133 may record theidentifying beacon parameters (e.g., MAC address, Major code and Minorcode) and the recorded beacon distance with the timestamp in a localdatabase 124 (308).

Where a chain of venues has their own beacons already installed, it maybe possible for these to act as the business beacons in the followingway.

1) The application 133 may be re-configured to listen additionally forthe entity UUID and/or the beacon UUID.

2) The beacon parameters (MAC address, Major and Minor codes) may beadded to the server database.

3) The application 133 may record the presence of the chain's beacons inthe usual way as described above.

The application 133 can be modified to use other formats. For example,other types of beacons may use different parameters (e.g., rather thanUUID, Major and Minor codes). For example, Eddystone beacons usenamespace and instance, and some embodiments may use Eddystone beaconswith namespace and instance parameters added to the server databaseinstead of UUID, Major and Minor codes.

The application 133 can be modified to subscribe to other APIs andrecord the presence of other external devices using the samemethodology. For example, WiFi hotspots could be issued to venues sothey can offer WiFi to their customers. Unique identifying details ofthe hotspots may be stored in the local database to record theirpresence.

FIG. 4 is a flowchart illustrating an example process for claiming avenue and registering a Bluetooth beacon. A user can claim a venue toadminister.

At 402-406, the user searches for their venue in the application 133(402), clicks a ‘Claim venue’ link (404) or similar, and then confirmsthat they are the administrator for the venue (406).

At 408, upon receiving the confirmation, the application 133 may send anAPI call to the server 120 with the user and venue IDs (408).

At 410, a postal letter containing a verification code in text and QRcode format may be sent to the address for the venue. Alternateprocesses could be used such as an automated telephone call to the phonenumber registered to the business or verification via a third-partyservice, for example. The venue details may be obtained from Googleplaces or some other data source, for example. The verification code maybe stored on the server (410).

At 412, on receipt of the letter, the user may scan the QR code, or typein the verification code text into the application 133.

At 414-426, the application 133 may send an API call to the server withthe user ID, venue ID and the verification code (414). The server 120may be configured to check if the user ID, venue ID and the verificationcode match the details of the corresponding data stored in the server(416). Upon determining there is a match (e.g., Yes at 416), the usermay be confirmed as the administrator of the venue, and these detailsmay be stored on the server (420). A success response may be sent to theapplication 133 (422). The application 133 may record the detailsincluding user ID as administrator of venue ID in the local database(424). The venue may be displayed in the user's list of venues theyadministrate (426). Otherwise, the server 120 may generate and send afailure response to the application 133, and the process may be aborted(418).

FIG. 5 is a flowchart illustrating an example process for registering abeacon.

At 502-504, a user can request a beacon and choose to receive aBluetooth beacon for a venue that they administer (502). The beacon maybe sent to the user. The beacon may be sent to the venue address viapost or delivery service. Once the user receives the beacon, they canregister it to their venue (504).

At 506, the user navigates to the administration page for the venue andchooses to add the beacon via an “add beacon” link via the application133 from from the venue's administration page.

At 508, the user may scan the QR code on the reverse of the beacon,which contains the serial number of the beacon and/or other identifyinginformation of the beacon, for example.

At 510-512, the application 133 may send the beacon serial number fromthe QR code to the server 120 via an API call (510) or other mechanism,and receives back the major code, minor code and MAC address associatedwith the beacon from the server (512).

At 514-516, the application 133 may store the beacon details in thelocal database (514) and instruct user to switch on the beacon (forexample, by removing battery isolation tab (516).

At 518, the application 133 waits to be notified of a detection eventfor the beacon by receiving a notification from the operating system orthe processor 131.

At 520, The application 133 may give the user visual confirmation onceit has verified the presence of the beacon (520).

At 522, the application 133 may instruct the user to place the beacon inits intended location (generally the centre of the venue, unlessmultiple beacons are being installed) and to walk to the venue exitwhich is nearest to the beacon (522).

At 524-526, once at the nearest exit, the user may press a button orotherwise issue a command in the application 133 (524). The application133 may calculate and takes an average of the distance to the beaconreported by the operating system's beacon detection API, using a numberof recorded distances (e.g., twenty recorded distances or some otherquantity) as the dataset (526) in some embodiments.

At 528, the application 133 may be executed by the processor 131 toobtain and record the beacon data, average distance, venue ID, and thelocation data of the user's mobile device.

At 530, the application 133 may be executed by the processor 131 to sendan API call or other communication to the server 120 with the beacondata, average distance, venue ID, and the location data of the user'smobile device. The location data of the user's mobile device may beobtained by the application 133 in the same way that location data isobtained in the normal use case above, for example.

At 532, the server 120 may update the database 124 to record that thebeacon is installed at the venue, and the location data for the placethe beacon was installed (beacon install location') and the range datacalculated in the above process.

An alternative approach for registering the beacon may include enablingthe application 133 to send the API call with the beacon physicalinstallation location and the beacon serial number. The server 120 maycheck the beacon location against the venue location (optionally withina tolerance level). If the beacon physical installation location doesnot match the venue location, the server 120 may send a failure responseto the application 133 of the mobile device 130, and the application 133may instruct the user to move to the correct location and try again.

FIG. 6 is a flowchart illustrating an example process for transmittingvisit data 125.

At 602-606, when the application 133 is loaded on the user mobile device130 by the user (602), and/or when a review is created by the user inthe application 133 (604), the application 133 may retrieve any visitdata 125 stored in the local database (606).

At 608-612, the application 133 may call an API on the server 120 tosend the visit data 125, which may be stored in a database 124 on theserver 120 (608). Once the data is successfully stored (610), the server120 may send a success response via the API to the application 133(612). Upon receiving the success response, the application 133 maydelete the data from the local database 124 to minimize data storagerequirements, or it may flag the data as having been sent.

FIG. 7 is a flowchart illustrating an example process for capturing areview created by a user.

At 702, a user may select venue from a map or search results. Forexample, the user selects a restaurant, bar, hotel, establishment,place, event or other significant location (a ‘venue’) displayed in amap view, or searches for a venue by name and/or location and selects aresult from the search.

At 704, the user may input their review (the ‘review data’). A user canadd one or more photos or videos (‘review media’). At least one photo orvideo may be required to create a review in some embodiments. Forexample, the user can take a photo or record a video natively in theapplication 133 (‘native capture’). The user can add a photo or videofrom their device's media storage, which was created outside theapplication 133 (‘media upload’).

At 706, the user can, in some embodiments optionally, input a shorttextual review. In some embodiments, the text may be limited to 500characters, although this character limit (or a word limit) may bedifferent in other embodiments. At 708, the user may give the venue arating score (e.g., between 1 and 5). At 710 and 712, the application133 may append to the review data the longitude and latitude datacaptured from the user's mobile device as the ‘review creation locationdata’ for the review and record a timestamp for the ‘review creation’event. This may be a separate operation in addition to the location dataof the mobile device captured by the application 133 as part of thevisit data 125.

At 714, the application 133 may call an API on the server 120 totransmit the review data and the review media. At 716, the review datamay be stored by the server 120 in a database, along with links to thereview media, which may be stored in the file system of the server.

At 718, the server 120 may process the review media to extract thelocation data and a timestamp from the EXIF data.

At 720, the server 120 may record the media data in the database alongwith media source about whether the review media was obtained by nativecapture or media upload (‘media source’).

FIG. 8 is a flowchart illustrating an example process for evaluating thedata to establish the review metrics. The elements of FIG. 8 may beperformed together or, in some embodiments, may be a set of separateprocesses that may be performed with or without one another. The visitdata 125 and the review data 126 may be analysed to establish thefollowing items, for example.

-   -   1) The review creation location data is analysed (802) and        compared to the location stored in the venue data 127 to        establish if the user was at the venue when the review was        created (‘review creation location match’) (804).    -   2) At 806-812, the media data may be analysed to establish:        -   i. Whether location of the media matches the venue location            (optionally, this can be within a tolerance level) (‘media            location match’) (808)        -   ii. Whether the media timestamp matches a record or records            from the visit data 125 (‘media timestamp match’) (810)        -   iii. Media source (‘native capture’ vs ‘media upload’) (812)    -   3) At 814, beacon data may be searched for one or more records        of the user in the presence of a venue's beacons within a        tolerance range. This may be established by looking for records        of beacon notification events that contain the user ID of the        person making the review, a beacon that is registered to the        venue, and a range from the beacon that is within the distance        set in the pairing process (optionally, this can be within a        tolerance level), for example. This may be stored as a binary        (yes/no) value or as an integer to record the number of records.    -   4) At 816-820, the processes and/or data may be established from        the retrieved record, including:        -   i. How long the user was at the venue on their most recent            visit (816);        -   ii. How many hours had elapsed from the end of their most            recent visit in the visit data 125 to the review creation            time (818);        -   iii. How many visits they have made to the venue (820).    -   5) The location data may be searched for one or more records of        the user at the venue location (‘location data match’) (822).        This may be established by searching for records of the user        location data which may include the user ID, and a latitude and        longitude that matches the location in the venue data 127        (optionally, this can be within a range of a tolerance level).        This may be stored as a binary (yes/no) value or as an integer        to record the number of records. In addition, the following        processes and or data may be established from the retrieved        records (822).        -   i. How long the user was at the venue on their most recent            visit (824).        -   ii. How many hours had elapsed from the end of their most            recent visit in the visit data 125 to the review creation            time (826).        -   iii. How many visits they have made to the venue (828).

An alternative approach to analyse visit data 125 in the review metricsmay include an approach wherein the range from the beacon in the beacondata is included in the review metrics rather than being used as afilter. This may become a factor that is available for the algorithm andmay be used to provide part of the granularity of the authority score.Similarly, a larger tolerance may be used with the location data, andthe distance from the venue location may be included in the reviewmetrics also, so that it may be used as a factor in the algorithm. Ifthe location data match and beacon data match values are being used asbinary (yes/no), the distances recorded under this approach may be forthe most recent visits for the relevant data set. If the location datamatch and beacon data match values are being used as integers to recordthe number of matches, the distances recorded for under this approachmay be averages of all visits for the relevant dataset.

Another alternative approach may include storing the visit data 125 astwo arrays in the review metrics, one for beacon data and another forlocation data. This may replace the beacon data match and location datamatch variables, and the number of visits. The distance from the beaconor the venue location (subject to any tolerance) may be used as a filterwhen creating these arrays, or the data could be included as anotherfactor for the algorithms.

The beacon data array may include: 1) the length of the visit; 2) thehours elapsed between the visit and the review creation time; and 3) theaverage distance from the beacon for the visit (if not used as afilter), for example.

The location data array may include: 1) the length of the visit; 2) thehours elapsed between the visit and the review creation time; 3) theaverage distance from the venue location for the visit (if not used as afilter), for example.

In some embodiments, alternative approaches to analyse media data in thereview metrics may be adjusted to accommodate for multiple photos orvideos. These approaches may provide more granularity for the algorithm.One approach may be to use integers to record the following data:

-   -   1) The media location match—set to the number of media records        that match the venue location;    -   2) The media timestamp match—set to the number of media records        where the timestamp matches a record or records from the visit        data 125;    -   3) Native capture—set to the number of media records where the        source is native capture; and    -   4) Media upload—set to the number of media records where the        source is media upload.

Another alternative approach may be to use an array with binary valuesfor each photo or video for:

-   -   1) Media location match;    -   2) Media timestamp match;    -   3) Native capture; and    -   4) Media upload.

In some embodiments, the authority score may be calculated by utilizingan algorithm. Example algorithms are described below, but they can bevaried to increase or decrease the importance of one or more of thefactors, or to omit or introduce factors. The algorithms may share thefollowing characteristics. They may establish an authority score with ahigh level of granularity, which may be used for the input to thedisplay element. The algorithms may utilize multiple factors of thereview metrics to achieve this granularity. For example, the followingfactors may be considered:

-   -   1) Whether there is a beacon data match;    -   2) Whether there is a review creation location match or location        data match;    -   3) How many hours have passed since the most recent visit        (either from beacon data or location data);    -   4) Whether there is media location match;    -   5) Whether the media source is native capture or media upload;        and    -   6) Whether there is a media timestamp match.

The algorithms may optionally use extrinsic data to further refine thescore. The extrinsic data may include:

-   -   1) Whether one or more beacons have been registered as present        at the venue by the venue administrator (‘beacon presence’).    -   2) The length of stay indicated for the user as a comparison to        the average length of stay for that venue, or that type of        venue. The score could be adjusted based on the variance from        the average. For example, an extremely short stay might be taken        as an indication that the user did not stay long enough to form        an authoritative opinion of the venue, and therefore reduce the        score.    -   3) The time of the visit could be compared to the opening hours        of the venue, and negatively adjust the score if the visit is        outside the opening hours.    -   4) The score could be adjusted if the user has visited a large        number of similar establishments and could be considered to have        a greater deal of comparative experience.

FIG. 9A is a flowchart of a process which emphasises beacon data matchesand location data matches and adjusts for recency of visit. FIG. 9B is aflowchart corresponding to FIG. 9A with example values. The algorithmmay include a method to distinguish a review creation location matchfrom a location data match. It may use media data as a secondary factor.

At 902, the authority score may be initially set to a base value ‘a’(for example, 0).

At 904, the review metrics value for review creation location match maybe checked to determine whether the review creation location matches thevenue location data.

-   -   1) If the review metrics confirm a review creation location        match (e.g., a “yes” at 904), an amount or value (for example,        “add 25” as shown in FIG. 9B) may be added to the score and the        process goes to step 908.    -   2) If the review metrics do not confirm a review creation        location match (e.g., a “no” at 904), the process goes to step        906.

At 906, if the review metrics confirm a location data match (e.g., a“yes” at step 906), an amount may be added to the score and adjusted forhow recent the latest visit was. An example calculation for this is:c*(1−(hours since visit)/d). Example values for c and d are 25 and 1000respectively.

If the review metrics do not confirm a location data match (e.g., a “no”at step 906), the score is not changed and the process goes to step 908.

At 908, the extrinsic data may be checked for beacon presence.

If the beacon presence is confirmed (e.g., a “yes” at step 908), thereview metrics may be checked for beacon data match (910).

-   -   1) If the beacon data match is confirmed (e.g., a “yes” at step        910), an amount may be added to the score, adjusted for how        recent the latest visit was. An example calculation for this is:        f*(1−(hours since visit)/g). Example values for f and g are 50        and 1000 respectively and the process goes to step 912.    -   2) If the beacon data match is not confirmed (e.g., a “no” at        step 910), an amount ‘e’ (for example 25) may be deducted from        the score and the process goes to step 912.

If the beacon presence is not confirmed (e.g., a “no” at step 908), thescore is left unchanged and the process goes to step 912.

At 912, the review metrics may be checked for the media source.

-   -   1) If the media source is native capture, an amount 7 (for        example 10) may be added to the score and the process goes to        step 914.    -   2) If the media source is media upload, then an amount or value        ‘h’ (for example 5) may be deducted from the score and the        process goes to step 914.

At 914, the review metrics may be checked for media location data match.

-   -   1) If the review metrics confirm a media location data match        (e.g., a “yes” at step 914), an amount or value ‘k’ (for        example 15) may be added to the authority score and the process        goes to step 916.    -   2) If the review metrics do not confirm a media location data        match (e.g., a “no” at step 914), an amount or value 7 (for        example 15) may be deducted from the authority score and the        process goes to step 916.

FIG. 10A is a flowchart similar to that illustrated in FIG. 9A whichalso adjusts for the length of the visit compared to the average lengthof visits. FIG. 10B is a flowchart corresponding to FIG. 10A withexample values.

At 1002-1014, an example algorithm B incorporates the example algorithmA in FIG. 9A as a base. The example algorithm B adds an extra step 1016to use extrinsic data to adjust the score.

At 1016, the length of the visit (from beacon data, or if not presentthen location data) may be compared to the average length of all visitsto the venue, to determine whether it is within a range of ‘l’-‘m’% (forexample 50-300%) compared to the average visit duration. At 1018,

-   -   1) if the length of the visit is within the range (e.g., a “yes”        at step 1016), the score is unchanged and may be returned to the        server 120.    -   2) If the length of the visit is outside the range (e.g., a “no”        at step 1016), an amount or value ‘n’ (for example 20) may be        deducted from the score. The deducted score may be returned to        the server 120.

FIG. 11A is a flowchart illustrating an example process for utilizing analgorithm C to give emphasis to reviews created within the applicationat the time of the visit rather than those added after the visit. FIG.11B is a flowchart corresponding to FIG. 11A with example values.Example C describes an algorithm that can be used to give more emphasisto reviews that are created live in the application 133 whilst at thevenue location, rather than added after the visit. It may use visit data125 as a secondary factor.

At 1102, the authority score may be initially set to a base value ‘a’(for example, “0” as shown in FIG. 11 B).

At 1104, the review metrics may be checked for the media source.

If the media source is native capture at 1104, an amount and value (forexample 20) may be added to the score, and the process goes to step1106. At 1106, the review metrics may be checked for media locationmatch.

-   -   1) If the review metrics confirm a media location match (e.g., a        “yes” at step 1106, an amount or value ‘c’ (for example 20) may        be added to the score.    -   2) If the review metrics do not confirm a media location match        (e.g., a “no” at step 1106, the score is left unchanged and the        process goes to step 1110.

At 1104, if the media source is media upload, the score is leftunchanged and the process goes on to step 1108.

At 1108, the review metrics may be checked for media location match.

-   -   1) If the review metrics confirm a media location match (e.g., a        “yes” at step 1108), an amount or value ‘d’ (for example 20) may        be added to the authority score.    -   2) If the review metrics do not confirm a media location match        (e.g., a “no” at step 1108), the score is left unchanged and the        process goes to step 1110.

At 1110, the review metrics may be checked for review creation locationmatch.

-   -   1) If the review metrics confirm a review creation location        match (e.g., a “yes” at step 1110), an amount or value ‘e’ (for        example 20) may be added to the score and the process goes to        step 1112.    -   2) If the review metrics do not confirm a review creation        location match (e.g., a “no” at step 1110), the score is        unchanged, and the process goes to step 1112.

At 1112, the review metrics may be checked for location data match.

-   -   1) If the review metrics confirm a location data match (e.g., a        “yes” at step 1112), the extrinsic may be checked for beacon        presence and the process goes to step 1114.    -   2) If the review metrics do not confirm a location data match        (e.g., a “no” at step 1112), the extrinsic data may be checked        for beacon presence and the process goes to step 1118.

At 1114, if the extrinsic data confirms beacon presence (e.g., a “yes”at step 1114), the process goes to step 1016.

-   -   1) At 1116, if the review confirm a beacon data match (e.g., a        “yes” at step 1116), an amount ‘h’ or value (for example 40) may        be added to the score, and the score may be returned to the        server 120 (1122).    -   2) At 1116, if the review metrics do not confirm a beacon data        match (e.g., a “no” at step 1116), an amount or value ‘g’ (for        example 10) may be added to the score, and the score may be        returned to the server 120 (1122).

At 1114, if the extrinsic data does not confirm beacon presence (e.g., a“no” at step 1114), an amount or value T (for example 20) may be addedto the score, and the score may be returned to the server 120 (1122).

At 1112, if the review metrics do not confirm location data match (e.g.,a “no” at step 1112), the extrinsic data may be checked for beaconpresence and the process goes to step 1118.

At 1118, if extrinsic data confirms beacon presence (e.g., a “yes” atstep 1118), the process goes to step 1120.

-   -   1) At 1120, if the review metrics confirm beacon data match        (e.g., a “yes” at step 1120), an amount (for example 40) may be        added to the score.    -   2) At 1120, if the review metrics do not confirm beacon data        match (e.g., a “no” at step 1120), the score is unchanged.

At 1122, the score may be returned to the server 120.

FIG. 12A is a flowchart illustrating an example process for utilizing anexample algorithm D similar to that illustrated in FIG. 9A but whichtakes a different approach to setting base scores. FIG. 12B is aflowchart corresponding to FIG. 12A with example values. The examplealgorithm D describes an algorithm that is similar in emphasis to theexample algorithm A in FIG. 9A, but takes a different approach andadjusts for recency once a base score has been established from the typeof visit data 125. Media data may be used as a secondary factor.

At 1202, the extrinsic data may be checked for beacon presence. If theextrinsic data confirms beacon presence (e.g., a “yes” at step 1202),the process goes to step 1204. If the extrinsic data does not confirmbeacon presence (e.g., a “no” at step 1202), the process goes to step1208.

At 1204, if the review metrics indicate a beacon data match (e.g., a“yes” at step 1204), the process goes to 1206.

-   -   1) At 1206, if the review metrics confirm a location data match        (e.g., a “yes” at step 1206), the score may be set to an amount        or value ‘f’ (for example 80) and the process goes to step 1212.    -   2) At 1206, if the review metrics do not confirm a location data        match (e.g., a “no” at step 1206), the score may be set to an        amount or value ‘e’ (for example 75) and the process goes to        step 1212.

At 1204, if the review metrics do not confirm a beacon data match (e.g.,a “no” at step 1204), the process goes to 1210.

-   -   1) At 1210, if the review metrics confirm a location data match        (e.g., a “yes” at step 1210), the score may be set to an amount        or value ‘d’ (for example 50) and the process goes to step 1212.    -   2) At 1210, if the review metrics do not confirm a location data        match (e.g., a “no” at step 1210), the score may be set to an        amount or value ‘a’ (for example 0) and the process goes to step        1212.    -   At 1208, if the extrinsic data does not confirm beacon presence        (e.g., a “no” at step 1202), the review metrics may be checked        for location data match.    -   1) At 1208, if the review metrics confirm location data match        (e.g., a “yes” at step 1208), the score may be set to an amount        or value ‘d’ (for example 65)    -   2) At 1208, if the review metrics do not confirm location data        match (e.g., a “no” at step 1208), the score may be set to an        amount or value ‘c’ (for example 0) and the process goes to step        1212.

At 1212, the score may be adjusted for recency by deducting the amountof hours since the most recent visit divided by 24. In the limbs wherethe score is set to values a or c (e.g., the “no” at step 1210 and the“no” at step 1208), there may be no visit data 125 and so no deductionis applied to the score at 1212. Further, the location data and beacondata may have different timestamps. It is the most recent visit from allvisit data 125 that may be used in this step.

At 1214, the review metrics may be checked for media location match.

-   -   1) If the review metrics confirm media location match (e.g., a        “yes” step at 1214), an amount or value ‘h’ (for example 10) may        be added to the score.    -   2) If the review metrics do not confirm media location match        (e.g., a “no” step at 1214), an amount or value ‘g’ (for        example 20) may be deducted from the score.

At 1216, the review metrics may be checked for the media source.

-   -   1) If the media source is native capture (e.g., a “yes” step at        1216), an amount or value 7 (for example 10) may be added to the        score.    -   2) If the media source is media upload (e.g., a “no” step at        1216), the score is unchanged.

At 1218, the score may be returned to the server 120.

Once the server has established the authority score, the authority scoremay be transmitted and saved to the database.

In the above algorithms, many processes use addition or subtractionvalues such as j and k to adjust scores. However, in some embodiments,any scores in any of the algorithms above could be left unchanged toalter the operation of the algorithms by setting the addition orsubtraction value to 0.

FIG. 13 is a flowchart illustrating an example process for displayingthe authority score and the user rating.

At 1302, the application 133 requests reviews of a venue via API fromthe server 120.

At 1304, in response to the request from the application 133, the server120 may return review data including user rating and the authority scorealong with and review media.

At 1306, the application 133 may receive the authority score and thereview data via the API and display the authority score along with theuser rating. The application 133 may be configured to construct agraphical representation of the user ratings as emblems with a group ofstars.

FIG. 14 shows an example graphical representation of the user ratings togenerate a visual indication of the authority score. The visualindication may have at least one visual characteristic determined by atleast one outcome of the calculation. The at least one visualcharacteristic may include a first shaded or colored area and a secondshaded or colored area, and wherein the calculation is configured sothat a contrast between the first shaded or colored area and the secondshaded or colored area increases as the authority score increases. theat least one visual characteristic comprises a first shaded or coloredarea and a background, and wherein the calculation is configured so thata visibility of the first shaded or colored area against the backgroundincreases as the authority score increases.

At 1308, the application 133 may be configured to add a visualrepresentation of the authority score by altering the opacity of thebackground.

At 1310, the application 133 may combine an emblem to be displayed aspart of the review.

In order to provide the end user with the rating that the reviewer gavethe venue and also the authority score as two separate pieces ofinformation, the end user may be required to consider both scores andmake a decision as to how to interpret them. There may be a number ofdrawbacks, including:

-   -   1) Increasing the amount of time takes the end user to establish        which reviews are authentic.    -   2) Giving the end user information overload, especially where        there a high number of reviews.    -   3) Potentially emphasising the review rating over the authority        score. For example, if the review rating was a series of stars,        and the authority score displayed as a percentage, the rating        may draw more attention, and result in the end user        inadvertently making a decision based on reviews with low        authority.

The authority score may be used to filter out reviews that are below athreshold, but this may be undesirable in some cases, as the existenceof the reviews with lower authority scores may be useful data for theend user. Thus, the end user should be able to see all reviews, andquickly and easily distinguish which ones they want to pay attention to.To accomplish this and aid understanding for the end user, the twoscores may be combined into one graphic representation.

An example of one method to achieve this is described below, and theratings may be as illustrated in FIG. 14.

-   -   1) The review rating may be displayed as a series of stars with        five stars being the highest rating, for example. The rating may        be displayed by setting the stars to a foreground colour of        white to reflect the rating score, and leaving them transparent        otherwise (although other colour combinations may be possible).        For example, a score of 3 out of 5 may have three stars with a        white foreground and two stars that are transparent. The stars        may have a solid border (in this example grey) which may be        bolder on the white stars.    -   2) The authority score may be displayed as a background to the        star rating. The background may have a bottom layer of white and        a top layer which is filled with a colour (in this example        orange). The opacity of the colour may be set based on the        authority score, divided by 100. Thus, an authority score of 100        may give an opacity of 1, which means that the background is        full-coloured, with no transparency. An authority score of 0 may        give an opacity of 0 and therefore the colour may be completely        transparent, and therefore display as white.    -   3) In this example, a review with a high authority score will        stand out visually, and the review rating will be easy to see.        Conversely, a review with a low authority score will fade into        the background, and the review rating will have less impact,        especially when the end user is scrolling quickly through the        reviews.

Alternative methods to display the authority score may include:

-   -   1) Using the authority score to vary the size of the review        rating emblem, so a high authority score may mean the review        rating is visually larger.    -   2) Using the authority score to display an authority bar as part        of the rating emblem, with the bar being the full width of the        emblem for an authority score of 100, reducing to no bar for an        authority score of 0.    -   3) Using the authority score to change the opacity of the        foreground colour of the review rating, so the stars (or other        emblem) change rather than the background.    -   4) Using the authority score to adjust the vertical fill of the        foreground in the rating emblem, for example, so the user rating        dictates how many stars are filled in with the foreground        colour, but the authority score dictates whether that foreground        colour goes from the bottom to the top of the star.    -   5) Using the authority score to change the colour of the        background.

Various processes and routines can be optionally implemented on theserver 120 to re-evaluate and update the authority scores of previousreviews on the basis of either aggregated data or extrinsic data.Factors that could be relevant may include:

-   -   1) Analysis of beacon data against beacon presence. Some        algorithms may downgrade the authority score if there is beacon        presence but no beacon data. However, a beacon may become        faulty, lose power, or be stolen—and therefore reviews would        have been downgraded unnecessarily. If all recent reviews, with        sufficient volume, for a venue show no beacon data despite it        having beacon presence, reviews after the last review with        beacon data could be re-evaluated on the basis of the venue not        having beacon presence.    -   2) Analysis of location data and beacon data against venue        location and beacon install location. If a beacon has been moved        to a new location in an attempt to provide falsely authentic        reviews, the relationship between location data and beacon data        may change. Some algorithms may prioritise beacon data over        location data. If all recent reviews, with sufficient volume,        show location data that is inconsistent with the venue location        or the beacon install location, reviews after the last review        where the data was consistent could be re-evaluated on the basis        of the venue not having beacon presence.    -   3) Age of reviews. Reviews from a number of years ago may no        longer be relevant, even though they were authoritative at the        time. Thus, authority scores may be degraded over time, by a        factor of time elapsed since the review was created.    -   4) User behaviour. A user may inadvertently add a review with a        low authority score. Or they may start to add low authority        reviews after adding a number of high authority reviews.        Calculation of the overall authority of a user's reviews could        be used to adjust the authority score of any outliers.

FIG. 15 is a block diagram of an example computing device 1500 that maybe utilized to execute embodiments to implement processes as describedherein. For example, computing device 1500 may be configured to providethe functionality and/or perform the processing described above.Computing device 1500 may be implemented on any electronic device thatruns software applications derived from compiled instructions, includingwithout limitation personal computers, servers, smart phones, mediaplayers, electronic tablets, game consoles, email devices, etc. In someembodiments, multiple computing devices 1500 may work together toprovide the functionality and/or perform the processing described above(e.g., facilitated by one or more network connections). In someimplementations, computing device 1500 may include one or moreprocessors 1502, one or more input devices 1504, one or more displaydevices 1506, one or more network interfaces 1508, and one or morecomputer-readable mediums 1510. Each of these components may be coupledby bus 1512, and in some embodiments, these components may bedistributed among multiple physical locations and coupled by a network.

Display device 1506 may be any known display technology, including butnot limited to display devices using Liquid Crystal Display (LCD) orLight Emitting Diode (LED) technology. Processor(s) 1502 may use anyknown processor technology, including but not limited to graphicsprocessors and multi-core processors. Input device 1504 may be any knowninput device technology, including but not limited to a keyboard(including a virtual keyboard), mouse, track ball, and touch-sensitivepad or display. Bus 1512 may be any known internal or external bustechnology, including but not limited to ISA, EISA, PCI, PCI Express,NuBus, USB, Serial ATA or FireWire. Computer-readable medium 1510 may beany medium that participates in providing instructions to processor(s)1502 for execution, including without limitation, non-volatile storagemedia (e.g., optical disks, magnetic disks, flash drives, etc.), orvolatile media (e.g., SDRAM, ROM, etc.).

Computer-readable medium 1510 may include various instructions 1514 forimplementing an operating system (e.g., Mac OS®, Windows®, Linux). Theoperating system may be multi-user, multiprocessing, multitasking,multithreading, real-time, and the like. The operating system mayperform basic tasks, including but not limited to: recognizing inputfrom input device 1504; sending output to display device 1506; keepingtrack of files and directories on computer-readable medium 1510;controlling peripheral devices (e.g., disk drives, printers, etc.) whichcan be controlled directly or through an I/O controller; and managingtraffic on bus 1512. Network communications instructions 1516 mayestablish and maintain network connections (e.g., software forimplementing communication protocols, such as TCP/IP, HTTP, Ethernet,telephony, etc.).

Review recordation and evaluation instructions 1518 may includeinstructions that enable computing device 1500 to provide functionalityand/or perform processing as described herein. Application(s) 1520 maybe an application that uses or implements the processes described hereinand/or other processes. The processes may also be implemented inoperating system 1515.

The described features may be implemented in one or more computerprograms that may be executable on a programmable system including atleast one programmable processor coupled to receive data andinstructions from, and to transmit data and instructions to, a datastorage system, at least one input device, and at least one outputdevice. A computer program is a set of instructions that can be used,directly or indirectly, in a computer to perform a certain activity orbring about a certain result. A computer program may be written in anyform of programming language (e.g., Objective-C, Java), includingcompiled or interpreted languages, and it may be deployed in any form,including as a stand-alone program or as a module, component,subroutine, or other unit suitable for use in a computing environment.

Suitable processors for the execution of a program of instructions mayinclude, by way of example, both general and special purposemicroprocessors, and the sole processor or one of multiple processors orcores, of any kind of computer. Generally, a processor may receiveinstructions and data from a read-only memory or a random-access memoryor both. The essential elements of a computer may include a processorfor executing instructions and one or more memories for storinginstructions and data. Generally, a computer may also include, or beoperatively coupled to communicate with, one or more mass storagedevices for storing data files; such devices include magnetic disks,such as internal hard disks and removable disks; magneto-optical disks;and optical disks. Storage devices suitable for tangibly embodyingcomputer program instructions and data may include all forms ofnon-volatile memory, including by way of example semiconductor memorydevices, such as EPROM, EEPROM, and flash memory devices; magnetic diskssuch as internal hard disks and removable disks; magneto-optical disks;and CD-ROM and DVD-ROM disks. The processor and the memory may besupplemented by, or incorporated in, ASICs (application-specificintegrated circuits).

To provide for interaction with a user, the features may be implementedon a computer having a display device such as an LED or LCD monitor fordisplaying information to the user and a keyboard and a pointing devicesuch as a mouse or a trackball by which the user can provide input tothe computer.

The features may be implemented in a computer system that includes aback-end component, such as a data server, or that includes a middlewarecomponent, such as an application server or an Internet server, or thatincludes a front-end component, such as a client computer having agraphical user interface or an Internet browser, or any combinationthereof. The components of the system may be connected by any form ormedium of digital data communication such as a communication network.Examples of communication networks include, e.g., a telephone network, aLAN, a WAN, and the computers and networks forming the Internet.

The computer system may include clients and servers. A client and servermay generally be remote from each other and may typically interactthrough a network. The relationship of client and server may arise byvirtue of computer programs running on the respective computers andhaving a client-server relationship to each other.

One or more features or steps of the disclosed embodiments may beimplemented using an API. An API may define one or more parameters thatare passed between a calling application and other software code (e.g.,an operating system, library routine, function) that provides a service,that provides data, or that performs an operation or a computation.

The API may be implemented as one or more calls in program code thatsend or receive one or more parameters through a parameter list or otherstructure based on a call convention defined in an API specificationdocument. A parameter may be a constant, a key, a data structure, anobject, an object class, a variable, a data type, a pointer, an array, alist, or another call. API calls and parameters may be implemented inany programming language. The programming language may define thevocabulary and calling convention that a programmer will employ toaccess functions supporting the API.

In some implementations, an API call may report to an application thecapabilities of a device running the application, such as inputcapability, output capability, processing capability, power capability,communications capability, etc.

While various embodiments have been described above, it should beunderstood that they have been presented by way of example and notlimitation. It will be apparent to persons skilled in the relevantart(s) that various changes in form and detail can be made thereinwithout departing from the spirit and scope. In fact, after reading theabove description, it will be apparent to one skilled in the relevantart(s) how to implement alternative embodiments. For example, othersteps may be provided, or steps may be eliminated, from the describedflows, and other components may be added to, or removed from, thedescribed systems. Accordingly, other implementations are within thescope of the following claims.

In addition, it should be understood that any figures which highlightthe functionality and advantages are presented for example purposesonly. The disclosed methodology and system are each sufficientlyflexible and configurable such that they may be utilized in ways otherthan that shown.

Although the term “at least one” may often be used in the specification,claims and drawings, the terms “a”, “an”, “the”, “said”, etc. alsosignify “at least one” or “the at least one” in the specification,claims and drawings.

Finally, it is the applicant's intent that only claims that include theexpress language “means for” or “step for” be interpreted under 35U.S.C. 112(f). Claims that do not expressly include the phrase “meansfor” or “step for” are not to be interpreted under 35 U.S.C. 112(f).

What is claimed is:
 1. A method of generating and displaying anauthority score, comprising: receiving, by at least one processor, visitdata indicative of a user's presence at a location; receiving, by the atleast one processor, review data describing an entity at the location;determining, by the at least one processor, an authority score for thereview data, the determining comprising performing a calculation usingat least a portion of the visit data as at least one input; generating,by the at least one processor, a visual indication of the authorityscore and the review data, the visual indication having at least onevisual characteristic determined by at least one outcome of thecalculation, wherein the at least one visual characteristic comprises afirst shaded or colored area of a first color indicating at least aportion of the review data and a second shaded or colored areacomprising a background layer of the first color and a foreground layerof a second color, and wherein the calculation is configured so that acontrast between the first shaded or colored area and the second shadedor colored area increases, through varying an opacity of the foregroundlayer, as a function of a degree of increase of the authority score; andcausing, by the at least one processor, the visual indication to bedisplayed by a display device.
 2. The method of claim 1, wherein thevisit data comprises an indication of the location, a duration of theuser's presence, a time of the user's presence, a record of a previousvisit, an activity performed at the location, an indication of a beacondetection by a client device at the location, or a combination thereof.3. The method of claim 2, wherein the determining comprises correlatingthe indication of the location with a record of the location of theentity.
 4. The method of claim 2, wherein the determining comprisescorrelating the beacon detection with a record of the location of theentity.
 5. The method of claim 2, wherein the calculation is configuredso that the authority score increases with an increase in the duration.6. The method of claim 2, wherein the calculation is configured so thatthe authority score decreases with an increase in a difference between atime at which the visit data is received and the time of the user'spresence.
 7. The method of claim 1, wherein the review data comprises atextual review, a rating score, a media element, or a combinationthereof.
 8. The method of claim 7, wherein the determining comprisesdetermining a location at which the media element was captured andcorrelating the location at which the media element was captured with arecord of the location of the entity.
 9. The method of claim 1, whereinthe function of the degree of increase is a linear function.
 10. Themethod of claim 1, wherein the second shaded or colored area comprises abackground.
 11. A system for generating and displaying an authorityscore, comprising: a display device; and at least one processor incommunication with the display device and configured to: receive visitdata indicative of a user's presence at a location; receive review datadescribing an entity at the location; determine an authority score forthe review data, the determining comprising performing a calculationusing at least a portion of the visit data as at least one input;generate a visual indication of the authority score and the review data,the visual indication having at least one visual characteristicdetermined by at least one outcome of the calculation, wherein the atleast one visual characteristic comprises a first shaded or colored areaof a first color indicating at least a portion of the review data and asecond shaded or colored area comprising a background layer of the firstcolor and a foreground layer of a second color, and wherein thecalculation is configured so that a contrast between the first shaded orcolored area and the second shaded or colored area increases, throughvarying an opacity of the foreground layer, as a function of a degree ofincrease of the authority score; and cause the visual indication to bedisplayed by the display device.
 12. The system of claim 11, wherein thevisit data comprises an indication of the location, a duration of theuser's presence, a time of the user's presence, a record of a previousvisit, an activity performed at the location, an indication of a beacondetection by a client device at the location, or a combination thereof.13. The system of claim 12, wherein the determining comprisescorrelating the indication of the location with a record of the locationof the entity.
 14. The system of claim 12, wherein the determiningcomprises correlating the beacon detection with a record of the locationof the entity.
 15. The system of claim 12, wherein the calculation isconfigured so that the authority score increases with an increase in theduration.
 16. The system of claim 12, wherein the calculation isconfigured so that the authority score decreases with an increase in adifference between a time at which the visit data is received and thetime of the user's presence.
 17. The system of claim 11, wherein thereview data comprises a textual review, a rating score, a media element,or a combination thereof.
 18. The system of claim 17, wherein thedetermining comprises determining a location at which the media elementwas captured and correlating the location at which the media element wascaptured with a record of the location of the entity.
 19. The system ofclaim 11, wherein the function of the degree of increase is a linearfunction.
 20. The system of claim 11, wherein the second shaded orcolored area comprises a background.
 21. A method of generating anddisplaying an authority score, comprising: receiving, by at least oneprocessor, review data describing an entity; determining, by the atleast one processor, an authority score for the review data; generating,by the at least one processor, a visual indication of the authorityscore and the review data, the visual indication having at least onevisual characteristic corresponding to at least one value of theauthority score, wherein the at least one visual characteristiccomprises a first shaded or colored area of a first color indicating atleast a portion of the review data and a second shaded or colored areacomprising a background layer of the first color and a foreground layerof a second color, and wherein the generating comprises increasing acontrast, through varying an opacity of the foreground layer, betweenthe first shaded or colored area and the second shaded or colored areaas a function of a degree of increase of the authority score; andcausing, by the at least one processor, the visual indication to bedisplayed by a display device.
 22. The method of claim 21, wherein thereview data comprises an indication of a location, a duration of auser's presence at the location, a time of the user's presence at thelocation, a record of a previous visit, an activity performed at thelocation, an indication of a beacon detection by a client device at thelocation, or a combination thereof.
 23. The method of claim 22, whereinthe determining comprises correlating the indication of the locationwith a record of the location of the entity.
 24. The method of claim 22,wherein the determining comprises correlating the beacon detection witha record of the location of the entity.
 25. The method of claim 22,wherein the determining comprises increasing the authority score with anincrease in the duration.
 26. The method of claim 22, wherein thedetermining comprises decreasing the authority score with an increase ina difference between a time at which the visit data is received and thetime of the user's presence.
 27. The method of claim 21, wherein thereview data comprises a textual review, a rating score, a media element,or a combination thereof.
 28. The method of claim 27, wherein thedetermining comprises determining a location at which the media elementwas captured and correlating the location at which the media element wascaptured with a record of the location of the entity.
 29. The method ofclaim 21, wherein function of the degree of increase is a linearfunction.
 30. The method of claim 21, wherein the second shaded orcolored area comprises a background.
 31. A system for generating anddisplaying an authority score, comprising: a display device; and atleast one processor in communication with the display device andconfigured to: receive review data describing an entity; determine anauthority score for the review data; generate a visual indication of theauthority score and the review data, the visual indication having atleast one visual characteristic corresponding to at least one value ofthe authority score, wherein the at least one visual characteristiccomprises a first shaded or colored area of a first color indicating atleast a portion of the review data and a second shaded or colored areacomprising a background layer of the first color and a foreground layerof a second color, and wherein the visual indication is generated byprocessing comprising increasing a contrast, through varying an opacityof the foreground layer, between the first shaded or colored area andthe second shaded or colored area as a function of a degree of increaseof the authority score; and cause the visual indication to be displayedby the display device.
 32. The system of claim 31, wherein the reviewdata comprises an indication of a location, a duration of a user'spresence at the location, a time of the user's presence at the location,a record of a previous visit, an activity performed at the location, anindication of a beacon detection by a client device at the location, ora combination thereof.
 33. The system of claim 32, wherein thedetermining comprises correlating the indication of the location with arecord of the location of the entity.
 34. The system of claim 32,wherein the determining comprises correlating the beacon detection witha record of the location of the entity.
 35. The system of claim 32,wherein the determining comprises increasing the authority score with anincrease in the duration.
 36. The system of claim 32, wherein thedetermining comprises decreasing the authority score with an increase ina difference between a time at which the visit data is received and thetime of the user's presence.
 37. The system of claim 31, wherein thereview data comprises a textual review, a rating score, a media element,or a combination thereof.
 38. The system of claim 37, wherein thedetermining comprises determining a location at which the media elementwas captured and correlating the location at which the media element wascaptured with a record of the location of the entity.
 39. The system ofclaim 31, wherein the function of the degree of increase is a linearfunction.
 40. The system of claim 31, wherein the second shaded orcolored area comprises a background.